This release features improvements to Tigris, the online workflow authoring tool which is part of LearnSphere.

Redesign of workflow list to allow for better navigation.

Returning users will recognize that the layout of the main workflows page has changed to allow for better navigation, both of their own and other's workflows. Users can now create folders in which to organize their workflows, choosing to group them by analysis methods, course or data type, for example.

Advanced search of workflows.

Also new to the main workflows page is an Advanced Search toolbox. The list of workflows can be filtered by owner, component, date range and access level for the data included in the workflow. The component search covers not only the component names and type (e.g., Analysis, Transform) but also workflow description, results and folders.

New visualization components.

Four new visualization components have been added: Scatter Plot, Bar Chart, Line Graph and Histogram. Each requires a tab-delimited file as input. The file must have column headers, but can contain numeric, date, or categorical data. In the example below, a DataShop student-step export is used with the Scatter Plot component to visualize the number of times a student has seen a problem vs. the amount of time it took to complete a step.

These visualization components produce dynamic content, allowing users to change both the variables that are being visualized in the output, as well as the look-and-feel of the graph, without having to re-run the entire workflow. The visualization can be downloaded as a PNG image file.

Private options.

Component developers may wish to have options that contain sensitive data, e.g., login information or keys. Examples of this are the ImportXAPI and Anonymize components. For instance, in the figure below you can see that the ImportXAPI component requires a URL for the data as well as the user id and password required to access the data. With support for private options, the component author can ensure that sensitive fields such as these are visible only to the workflow owner, while other options default to 'public' and are visible to all users.

WebServices for LearnSphere.

With this release you can use Web Services to programmatically retrieve LearnSphere data, including lists of workflows, as well as attributes and results for specific workflows. In the next release this functionality will be extended to allow users to create, modify and run workflows programmatically as well.

Ability to link a workflow to one or more datasets.

Creating a workflow from a DataShop dataset will establish a relationship between the dataset and workflow. However users may wish to link multiple datasets to a workflow and they may want to do this only after creating the workflow. There is a new "Link" icon on each workflow page that opens a dialog listing datasets that can be referenced; this is available to the workflow owner. Users viewing the workflow can click on the "datasets" link below the workflow name to see which datasets have been linked to the workflow.

Unique URL for each workflow gives ability to link directly to a workflow.

To facilitate easy sharing of workflows, each workflow now has unique URL. The URL can also be bookmarked.

In addition to the above changes, there are several component improvements.

The R-based iAFM and Linear Modeling components have been optimized, resulting in marked performance improvements.

Learning Curve categorization. A new feature, enabled by default, categorizes the learning curves (graphs of error rate over time for different KCs, or skills) generated by this visualization component into one of four categories. This can help to identify areas for improvement in the KC model or student instruction. Learn more about the categories here.

The OutputComparator now allows for multiple matching conditions.

There is a new component -- OLI LO to KC -- that can be used to map learning objectives for an OLI course into DataShop KC models. The component builds a KC model import for a given OLI skill model.

The output format for the PythonAFM component is now XML, making it easier to use in the OutputComparator.

The TextConverter component has been extended so that XML, tab-delimited and comma-separated (CSV) inputs can be converted to either tab-delimited or CSV outputs.